대한전자공학회논문지SP (Journal of the Institute of Electronics Engineers of Korea SP)

대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지

개선된 S-curve 모델과 RGB 칼라 LUT를 이용한 모니터와 모바일 디스플레이 장치간 색 정합

Color matching between monitor and mobile display device using improved S-curve model and RGB color LUT

  • 박기현 (경북대학교 전자전기컴퓨터학부) ;
  • 이명영 (경북대학교 전자전기컴퓨터학부) ;
  • 이철희 (안동대학교 컴퓨터공학전공) ;
  • 하영호 (경북대학교 전자전기컴퓨터학부)
  • 발행 : 2004.11.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 논문에서는 모니터와 모바일 디스플레이간의 복잡한 색 정합 과정을 단순화시키는 3차원의 색 정합 look-up table(LUT)을 설계하였다. 색 정합을 위해서는 우선 영상의 색을 CIEXYZ 혹은 CIELAB 등의 장치 독립적인 색 공간에서 처리하여야 한다. 장치 의존적인 RGB 색 공간의 데이터에서 장치 독립적인 색 공간의 데이터를 얻기 위해서는 디스플레이 특성화 과정이 필요하다. 기존의 S-curve 모델을 이용하여 LCD를 특성화 하면 LCD의 비선형적인 계조 특성으로 인해 특성화 오차가 허용 오차보다 커지게 된다. 본 논문에서는 X, Y, Z의 전기-빛 입출력 특성을 이용하여 S-curve 모델의 특성화 오차를 줄였다. 또한 모니터와 모바일 디스플레이간의 색 정합을 수행함으로써 색 표현력이 향상된 영상을 모바일 디스플레이에서 획득할 수 있었으며, 실험을 통하여 허용오차 내의 색 정합 LUT의 최소 크기가 64(4×4×4)라는 것을 확인하였다.

This paper proposes a color matching 3D look-up table simplifying the complex color matching procedure between a monitor and a mobile display device. In other to perform color matching, it is necessary to process color of image in the device independent color space like CIEXYZ or CIELAB. To obtain the data of the device independent color space from that of the device dependent RGB color space, we must perform display characterizations. LCD characterization error using S-curve model is larger than tolerance error since LCD is more nonlinear than CRT. This paper improves the S-curve model to have smaller characterization error than tolerance error using the electro-optical transfer functions of X, Y, and Z value. We obtained images having higher color fidelity on mobile display devices through color matching experiments between monitor and mobile display devices. As a result of this experiments, we concluded that the color matching look-up table with 64(4${\times}$4${\times}$4) is the smallest size allowing characterization error to be acceptable.

키워드

참고문헌

  1. K. E. Spaulding, R. N. Ellson, and J. R. Sullivan, 'UltraColor: A new gamut mapping strategy,' Device-independent Color Imaging II, vol. 2414, pp. 61-68, 1995 https://doi.org/10.1117/12.206553
  2. E. D. Montag and M. D. Fairchild, 'Psychophysical evaluation of gamut mapping techniques using simple rendered images and artificial gamut boundaries,' IEEE Transactions on Image Processing, vol. 6, no. 7, pp. 977-989, July 1997 https://doi.org/10.1109/83.597273
  3. J. Morovic, 'To develop a universal colour gamut mapping algorithm,' PhD. Thesis, University of Dervy, U. K, Oct. 1998
  4. N. Katoh, M. Ito, and S. Ohno, 'Three-dimensional gamut mapping using various color difference formulae and color spaces,' Journal of Electronic Imaging, vol. 8, pp. 365-379, Oct. 1999 https://doi.org/10.1117/1.482705
  5. P. G. Herzog and H. Buring, 'Optimizing gamut mapping: Lightness and hue adjustment,' Journal of Imaging Science and Technology, vol. 44, no. 4, pp. 334-342, July/Aug. 2000
  6. C. S. Lee, C. H. Lee, and Y. H. Ha, 'Parametric gamut mapping algorithms using variable anchor points,' Journal of Imaging Science and Technology, vol. 44, no. 1, pp. 68-73, Jan./Feb. 2000
  7. J. Morovic and M. R. Luo, 'Evaluation gamut mapping algorithms for universal applicability,' Color Research and Application, vol. 26, no. 1, pp. 85-102, Feb. 2001 https://doi.org/10.1002/1520-6378(200102)26:1<85::AID-COL9>3.0.CO;2-2
  8. C. S. Lee, Y. W. Park, S. J. Cho, and Y. H. Ha, 'Gamut mapping algorithm using lightness mapping and multiple anchor points for linear tone and maximum chroma reproduction,' Journal of Imaging Science and Technology, vol. 45, no. 3, pp. 209-223, May/June 2001
  9. H. S. Chen and H. Kotera, 'Three-dimensional gamut mapping method based on the concept of image dependence,' Journal of Imaging Science and Technology, vol. 46, no. 1, Jan/Feb. 2002
  10. R. S. Berns, R. J. Motta, and M. E. Gorzynski, 'CRT Colorimetry. Part I: Theory and Practice,' Color Research and Application, vol. 18, no. 5, pp. 299-314, Oct. 1993 https://doi.org/10.1002/col.5080180504
  11. R. S. Berns, M. E. Gorzynski, and R. J. Motta, 'CRT Colorimetry. Part II: Metrology,' Color Research and Application, vol. 18, no. 5, pp. 315-325, Oct. 1993 https://doi.org/10.1002/col.5080180505
  12. R. S. Berns, 'Methods for characterizing CRT displays,' Displays, vol. 16, no. 4, pp. 173-182, May 1996 https://doi.org/10.1016/0141-9382(96)01011-6
  13. Y. S. Kwak and L. W. MacDonald, 'Characterisation of a desktop LCD projector,' Displays, vol. 21, no. 5, pp. 179-194, Dec. 2000 https://doi.org/10.1016/S0141-9382(00)00049-4
  14. Y. S. Kwak and L. W. MacDonald, 'Accurate prediction of color liquid crystal displays,' Ninth Color Imaging Conference: Color Science and Engineering, Scottsdale, U.S.A., pp. 355-359, Nov. 2001
  15. H. R. Kang, Color Technology for Electronic Image Device, SPIE Optical Engineering Press, 1996
  16. P. C. Hung, 'Colorimetric calibration in electronic imaging devices using a look-up-table model and interpolation,' Journal of Electronic Imaging, vol. 36, no. 1, pp. 53-61, Jan. 1993 https://doi.org/10.1117/12.132391
  17. M. D. Fairchild, Color Appearance Models, Addison-Wesley, 1998
  18. J. Y. Hardeberg, Acquisition and reproduction of color Images: Colorimetric and multispectral approaches, Dissertation.com, 2001